New nonlinear regression modeling and multi-objective optimization of cutting parameters in drilling of GFRE composites to minimize delamination

摘要

This work focuses on optimization of the cutting parameters to minimize delamination resulting from drilling of woven roving Glass Fiber-Reinforced Epoxy (GFRE) laminates, using sequential quadratic programming algorithm based on new developed multiple nonlinear regression models. The influence of drilling parameters namely; speed, feed and drill pre-wear on drilling response variables namely; thrust force, torque, peel-up delamination and push-out delamination of GFRE composites has been analyzed through 3D plots. Analysis of variance (ANOVA) was employed to study the influence of drilling parameters on drilling response variables. From the experimental results and ANOVA, it was observed that drilling response variables are most influenced by feed and drill pre-wear, while the effect of speed is relatively insignificant. The conclusion of the multiple objective optimization revealed that, high rotational speed and low feed rate are the optimum drilling parameters for most of the drilling response variables.